量化交易-课设-基于Informer的股票价格预测(报告+代码)

上传者: 43607525 | 上传时间: 2025-03-31 21:53:12 | 文件大小: 4.04MB | 文件类型: RAR
这篇论文探讨了深度学习在股票价格预测方面的应用。股票市场受多种因素的影响,准确地预测股票价格对于市场经济和投资者来说至关重要。然而,传统的统计学方法在处理股票价格数据时存在一些困难,因此研究者们转向了深度学习模型,这些模型具有强大的数据表示和学习能力。 为了实现股票价格预测,研究者们采用了基于数据和基于文本的方法,并结合了各种深度神经网络模型进行分析。文章详细介绍了Informer方案的架构和模型构建过程。Informer方案是一种基于Transformer架构的深度学习模型,它能够有效地捕捉股票市场中的复杂模式和关联性。 通过采用深度学习方法,股票预测的准确性和效果有望得到提高,为投资决策提供更可靠的支持。深度学习模型能够自动学习数据中的特征,并从大量的历史数据中发现潜在的模式和趋势。这使得投资者能够更好地理解市场动态,做出更明智的决策。 总之,深度学习在股票价格预测中的应用具有巨大的潜力。这项研究为改进股票预测方法提供了有益的思路,并为投资者提供了一种新的工具,帮助他们更好地理解和应对股票市场的挑战

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